code: def make_layers(in_channels, cfg, stride=1, rate=1):
      layers = []
      for v in cfg:
          if v == "M":
              layers += [nn.MaxPool2d(kernel_size=2, stride=2)]
          else:
              conv2d = nn.Conv2d(
                  in_channels,
                  v,
                  kernel_size=3,
                  padding=1,
                  stride=stride,
                  dilation=rate,
              )
              layers += [conv2d, nn.ReLU(inplace=True)]
              in_channels = v
      return nn.Sequential(*layers)
  
imports: import torch
  import torch.nn
  from torchvision.models._utils import IntermediateLayerGetter
  from torch.hub import load_state_dict_from_url
  from torchvision.models.resnet import BasicBlock
label_desc: Use image node_id 3 for calling the VGG obj's underlying member method code with example usage: obj.make_layers(in_channels, cfg, stride, rate) and returns: nn